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Presentation
Presentation
Statistics provides methods for collecting, organising, describing, analysing and interpreting data used in market research, consumer behaviour, customer segmentation, campaign evaluation and sales analysis. In the field of marketing, these methods enable data to be transformed into information that supports the formulation, implementation and evaluation of strategies. In this module, students develop the skills to apply descriptive and inferential statistical techniques to the analysis of marketing problems, interpret quantitative results, identify patterns and relationships between variables, and support decisions based on empirical evidence.
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Class from course
Class from course
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Degree | Semesters | ECTS
Degree | Semesters | ECTS
Bachelor | Semestral | 4
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Year | Nature | Language
Year | Nature | Language
1 | Mandatory | Português
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Code
Code
ULHT168-194
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Prerequisites and corequisites
Prerequisites and corequisites
Not applicable
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Professional Internship
Professional Internship
Não
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Syllabus
Syllabus
Basic applications in Statistics; Data collection and sampling; Measures of Descriptive Statistics; Data organization: graphs and tables; Probabilities; Introduction to Statistical Inference; Linear correlation and linear regression.
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Objectives
Objectives
The course aims to develop data analysis skills, enabling students to apply statistical techniques to solve marketing problems. At the end of the course, students should be able to: Understand and calculate measures of central tendency, dispersion, percentiles, quartiles, deciles, and distribution measures. Use descriptive statistical methods, both numerical and graphical, to interpret data sets. Recognize and apply basic probability concepts in problem solving. Calculate fundamental parameters such as mean deviation, variance, and standard deviation. Understand and apply concepts of correlation and linear regression in practical contexts. Analyse and apply hypothesis tests, including Student's t-test, to compare means and support data-driven decision-making.
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Teaching methodologies
Teaching methodologies
Problem-Based Learning (PBL). With this approach, the program aims to engage students in purposeful learning experiences, encouraging them to tackle authentic and relevant challenges of the present. Students are prompted to apply critical thinking throughout the investigative process. This methodology fosters essential skills for both academic and professional contexts, enhancing their learning journey.
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References
References
Agresti, A., Franklin, C. A., & Klingenberg, B. (2021). Statistics: The Art and Science of Learning from Data, Global Edition. Bispo, R., & Maroco, J. (2005). Estatística Aplicada às Ciências Sociais e Humanas. 2a Edição. Climepsi Editores. Barroso, M., Sampaio, E., & Ramos, M. (2010). Exercícios de Estatística Descritiva para as Ciências Sociais. 2a Edição. Edições Silabo. Healey, J. F., & Donoghue, C. (2020). Statistics: A Tool for Social Research and Data Analysis. Cengage Learning. Mazzocchi, M. (2008). Statistics for marketing and consumer research. SAGE. Murteira, B., Ribeiro, C. S., Silva, J. A., & Pimenta, C. (2023). Introdução à Estatística. 4a Edição. Escolar Editora. Reis, E., Melo, P., Andrade, R., & Calapez, T. (2021). Estatística Aplicada (volume 1). 7a Edição. Edições Sílabo.
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Assessment
Assessment
Descrição
Ponderação
Exercícios
10%
Primeira frequência
40%
Segunda frequência
50%
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Mobility
Mobility
No





